• The Journal of Information Systems
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• v.28 no.2
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• pp.73-92
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• 2019

Purpose This study conducted an empirical study on the influence of institutional mechanisms on the formation of customer trust among leading online businesses. This study focused on the construct of PEEIM(Perceived Effectiveness of e-Commerce Institutional Mechanisms) which is the perceived recognition of institutional mechanisms for e-Commerce in general and the construct of PEIS which is the perceived recognition of institutional mechanisms that are implemented by vendors. Design/methodology/approach The online and offline surveys were conducted for the leading online shopping vendors in Korea and 292 data were used for the empirical analysis. The research model was tested using partial least squares structural equation modeling (PLS-SEM) in this study. The full measurement model including the formative second-order constructs was examined with the exploratory factor analysis. The structural model was analyzed via a two-stage approach. To analyze the research model this study used Smart PLS 2.0 program. Findings The findings showed that PEEIM negatively moderates the relationship between satisfaction in vender and trust in vender, but had no moderating effect between trust in vender and repurchase intention. In addition, the institutional mechanisms of vendors(PEIS) have been shown to have a direct impact on the vender's trust.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.21-49
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• 2008

The area of the internet shopping mall heavily relies on new emerging information technologies, and it essentially requires delicate marketing model to support consumer behavior. RSS, which is one of the representative Web 2.0 technologies, is the system that distributes digital contents without any Web browser. RSS is expected not only to be very useful in online marketing but also to become actively applied on various areas such as online newspapers and blogs. AISAS model was proposed to complement the AIDMA model that did not cover the new changing customer behaviors of online commerce environment such as search and share. In this research, we propose a marketing model which utilizes RSS based on the AISAS model to support internet shopping malls. With our marketing model, internet shopping malls are expected to provide required services to the customers at every AISAS step. Moreover, it can provide integrated services by connecting all service components of each step. We utilized RSS in our model to implement those services because RSS has many advantages on supporting search and share of product information.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.189-196
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• 2020

In this paper, we propose a study on the purchasing intent of the new e-commerce consumer, the coronavirus may once again drive the structural change of China's economy, and the new online marketing model will be noticed during the epidemic. Through 438 questionnaires collected on the Internet, frequency analysis, element analysis, reliability analysis and structural equation analysis were performed using SPSS V22.0 and AMOS V22.0 methods. Study the validation of hypotheses in the model to reveal the reasons why consumers in the new e-business are exposed. The results show that e-commerce features of Internet celebrities and individual characteristics of Internet celebrities can only enhance consumers' satisfaction. Quasi social relationships only increase consumer satisfaction without generating the will to purchase directly. Consumer satisfaction is the core foundation that dominates long-term consumption. E-commerce should focus on the ability of online celebrities to sell their expertise and the adaptability of value and product characteristics when conducting online celebrity marketing.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.25
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• pp.211-241
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• 2005

Innovation resistance toward technology products such as e-Marketplace is an important concept in business to business marketing. But most of researches and literatures have not been focused on innovation resistance. Therefore, the objective of this paper is to confirm key factors that effects on the innovation resistance. Additionally this study will be revealed the factors affecting the innovation resistance to information technology of trade according to adopting stage. Based on the past literatures, the innovation resistance of users can be viewed as dependent on two sets of factors came from the study of Innovation Resistance Model(Ram, 1987):perceived innovation(e-Marketplace) characteristics and user(trading company) characteristics. Perceived innovation characteristics consists of relative advantage, compatibility, perceived risk, complexity, inhibitory effect on the adoption of profitable innovation. The user characteristics consist of innovativeness, beliefs and attitude toward existing trade method. And user adoption stage came from the study of Innovation Diffusion(Roger, 1995). To make it simple, this study divides group1(knowledge/persuasion/decision) and group2(implementation/confirmation). In the result of the empirical study, the hypothesis 1, hypothesis 2, hypothesis 4 were supported partially and hypothesis 3 was completely supported.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.169-175
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• 2019

Service quality has been a point of discussion from the decades as it is important for customer satisfaction, loyalty and retention. Various models have been proposed to measure the quality in the service sector. Models are modified in accordance with context and geography to assess the quality of service better. This study aims to investigate the impact of the modified e-SERVQUAL model on the customer perception about the existing relation and potential scope of doing business with a bank which in-turn will decide the performance of the bank. Statistical data was analyzed through various tests like reliability analysis, correlation and regression analysis using SPSS 25.0. The primary data of e-SQ and performance was gathered from 721 internet banking users using 32 item questionnaire, representing 72% response rates, of four selected Islamic banks of Malaysia. E-SERQUAL was modified by adding Shariah Compliance information about banks and products for Islamic banking customers. The finding specified that efficient & reliable services, fulfillment, security/trust, and Shariah compliance information have a significant association with the performance of Islamic banks. The research is original and its implications will be helpful for Islamic banks across the world to enhance the online experience of customers, which will help them to retain the customers in the rapid changing virtual environment.

• Journal of Distribution Science
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• v.22 no.1
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• pp.79-94
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• 2024

Purpose: The popularity of social media has altered how customers interact with businesses, and an increasing number of customers prefer to voice their complaints on social media. Bystanders can observe the customer complaint process on social media, but the impact of transparency on bystanders remains uncertain. Therefore, this study established and verified a model for defining the effect of transparency and service recovery types on bystanders. Research Design and Methodology: In this study, we used the internet survey platform "So Jump" to collect data. And we validated three studies with SPSS 26.0 and Smart PLS 4.0. Result: First, we showed that the transparency process (vs. result) is more likely to increase customer forgiveness and E-loyalty and reduce E-NWOM intention among bystanders. Second, customer forgiveness also plays a complementary mediating role between transparency and E-loyalty, as well as between transparency and E-NWOM intention. Finally, we found a modest interaction effect between transparency (process vs. result) and service recovery types (psychological vs. tangible vs. hybrid) on bystanders' customer forgiveness and E-loyalty. Conclusions: This study provides actionable recommendations for how service managers can effectively employ social media as a means for distributing feedback information to manage service recovery in the future.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.135-153
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• 2007

As a system integration framework, the role of SOA(Service Oriented Architecture) is widening and increasing day by day. The SOA framework enables software applications or computing resources to integrate flexibly and to provide more various business models. But, it is strongly required of SOA service level management for applying SOA in real business world. In this respect, we need a study on method for managing SOA system for keeping higher quality of SOA. This paper provides a new management method for SOA service level by analyzing quality factors in Web services, as SOA implementation, and negotiation/contract according to SLA methodology.

• International Commerce and Information Review
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• v.14 no.1
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• pp.369-390
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• 2012

According to diffusion of social network, social commerce based this platform have been rapidly growing with usage of multiple smart devices. In this paper, we review several definitions & classifications of social commerce, and then suggest our definition. Above all, we suggest social commerce model analysis framework in perspective of business model based on revised Timmers's definition. With this framework, we analyzes impact of social commerce on e-commerce in perspective of value, actor, and revenue models. Through this analysis, we can find social commerce impact and change existing e-commerce. Finally, we suggest implications of social commerce, future directions of social commerce, further research issues. Through this research, we expect that actors related to e-commerce have the strategic implications.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• Proceedings of the CALSEC Conference
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• 1997.11a
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• pp.269-286
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• 1997

This paper presents the results of analysis for the Flexible Computer Integrated construction(FCIC) system to adapt CALS on the construction industry- Acquisition and supply process of the system are represented by IDEF0 function models and FCIC information systems are briefly described in this paper. The model presented here used as a reference for the development of CALS system.